Finite-/fixed-time anti-synchronization of neural networks with leakage delays under discontinuous disturbances

Lian Duan, Jinzhi Liu, Chuangxia Huang and Zengyun Wang

Chaos, Solitons & Fractals, 2022, vol. 155, issue C

Abstract: This paper is concerned with the finite-/fixed-time anti-synchronization (FFTAS) problem of neural networks with leakage delays under discontinuous disturbances. By designing new negative exponential controllers, in light of Fillipov’s theory and the Lyapunov functional method, novel FFTAS criteria are established for the considered drive-response network systems, the corresponding settling time is estimated as well. The established theoretical results extend and cover the existed ones. In addition, a numerical example is given to verify the practicability of the obtained results.

Keywords: Neural network; Leakage delay; Discontinuous activation; Finite-/fixed-time anti-synchronization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:155:y:2022:i:c:s0960077921009930

DOI: 10.1016/j.chaos.2021.111639

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